The fully synthetic neuroimaging dataset generated for analysis of fully synthetic data in the current study are available as Research Data from Mendeley Data. Ten fully synthetic datasets are included, with synthetic gray matter images (nifti files) that were generated based on simulated participant data (text files). The file Synthetic_predictors.tar.gz contains ten fully synthetic predictor tables with information for 264 simulated subjects. Due to large file sizes, a separate archive was created for each set of synthetic gray matter image data: RBS001.tar.gz, …, RBS010.tar.gz. Regression analyses were performed for each synthetic dataset, then average statistic maps were made for each contrast, which were then smoothed (see accompanying...
The rise of neuroimaging in the last years has provided physicians and radiologist with the ability ...
The CSV file contains the cortical thickness (CT) and fractal dimension (FD) estimated from the brai...
Deep Learning (DL)-based segmentation methods have been quite successful in various medical imaging ...
The dataset is made primarily for the task of real-time low latency filtering of the EEG data in the...
Statistical analysis techniques for highly complex structured data such as fMRI data should be thoro...
This archive contains sample output files for the sample data accompanying the Princeton Handbook fo...
Large amounts of multimodal neuroimaging data are acquired every year worldwide. In order to extract...
This archive is a supplement for the 99 simulated brains dataset http://dx.doi.org/10.6097/e230-2020...
328 pagesTwo brain activity recording paradigms in humans have emerged as increasingly more popular ...
AbstractLarge amounts of multimodal neuroimaging data are acquired every year worldwide. In order to...
Background. Datasets consisting of synthetic neural data generated with quantifiable and controlled ...
Magnetic resonance imaging (MRI) in neuroscience is one of the most powerful non-invasivemethods to ...
This data set was analysed for the publication "Acoustic and higher-level representations of natural...
Historically, our understanding of the human brain has been mutually affected both by the available ...
A primary focus of neuroscience is understanding how information about the world is encoded in the a...
The rise of neuroimaging in the last years has provided physicians and radiologist with the ability ...
The CSV file contains the cortical thickness (CT) and fractal dimension (FD) estimated from the brai...
Deep Learning (DL)-based segmentation methods have been quite successful in various medical imaging ...
The dataset is made primarily for the task of real-time low latency filtering of the EEG data in the...
Statistical analysis techniques for highly complex structured data such as fMRI data should be thoro...
This archive contains sample output files for the sample data accompanying the Princeton Handbook fo...
Large amounts of multimodal neuroimaging data are acquired every year worldwide. In order to extract...
This archive is a supplement for the 99 simulated brains dataset http://dx.doi.org/10.6097/e230-2020...
328 pagesTwo brain activity recording paradigms in humans have emerged as increasingly more popular ...
AbstractLarge amounts of multimodal neuroimaging data are acquired every year worldwide. In order to...
Background. Datasets consisting of synthetic neural data generated with quantifiable and controlled ...
Magnetic resonance imaging (MRI) in neuroscience is one of the most powerful non-invasivemethods to ...
This data set was analysed for the publication "Acoustic and higher-level representations of natural...
Historically, our understanding of the human brain has been mutually affected both by the available ...
A primary focus of neuroscience is understanding how information about the world is encoded in the a...
The rise of neuroimaging in the last years has provided physicians and radiologist with the ability ...
The CSV file contains the cortical thickness (CT) and fractal dimension (FD) estimated from the brai...
Deep Learning (DL)-based segmentation methods have been quite successful in various medical imaging ...